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    <title>Text Classfication Results Show</title>

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    <caption>
       <b>Path to code</b>
    </caption>
    <tr>
        <td>thucnews</td>
        <td>
            <a href="https://gitee.com/study234/fnlp/blob/master/jiquanquan/tests/text_classification/thucnews_text_classification.ipynb">
                /tests/text_classification/thucnews_text_classfication.ipynb
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        <td>imdb</td>
        <td>
            <a href="https://gitee.com/study234/fnlp/blob/master/jiquanquan/tests/text_classification/imdb_text_classification.ipynb
">
                /tests/text_classification/imdb_text_classfication.ipynb
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    <caption>
        <b>Presentation of classification results of different models under different text data</b>
    </caption>
    <tr>
        <td align="center">
            <a href="./summary_results/text_classification.xlsx" download="text_classification.xlsx">download</a>
        </td>
        <td colspan="3" align="center">Thucnews</td>
        <td colspan="3" align="center">IMDB</td>
    </tr>
    <tr>
        <td>Model</td>
        <td>Precision</td>
        <td>Recall</td>
        <td>F-Measue</td>
        <td>Precision</td>
        <td>Recall</td>
        <td>F-Measue</td>
    </tr>
    <tr>
        <td>MultinomialNB</td>
        <td>0.95241583</td>
        <td>0.951815385</td>
        <td>0.951846952</td>
        <td>0.832640661</td>
        <td>0.83264</td>
        <td>0.832639563</td>
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        <td>BernoulliNB</td>
        <td>0.922462101</td>
        <td>0.9216</td>
        <td>0.921640263</td>
        <td>0.826052859</td>
        <td>0.82432</td>
        <td>0.824456445</td>
    </tr>
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        <td>ComplementNB</td>
        <td>0.951772911</td>
        <td>0.950646154</td>
        <td>0.950842409</td>
        <td>0.832640031</td>
        <td>0.83264</td>
        <td>0.832639674</td>
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        <td>DecisionTree</td>
        <td>0.900310264</td>
        <td>0.900676923</td>
        <td>0.900447698</td>
        <td>0.727258207</td>
        <td>0.7272</td>
        <td>0.727203618</td>
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        <td>Kneighbors</td>
        <td>0.916269839</td>
        <td>0.915261538</td>
        <td>0.915424521</td>
        <td>0.767193455</td>
        <td>0.76264</td>
        <td>0.763213382</td>
    </tr>
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        <td>MLP</td>
        <td>0.965119088</td>
        <td>0.965107692</td>
        <td>0.965084838</td>
        <td>0.879121125</td>
        <td>0.87912</td>
        <td>0.879120287</td>
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        <td>RandomForest</td>
        <td>0.897780631</td>
        <td>0.895938462</td>
        <td>0.895908858</td>
        <td>0.781824103</td>
        <td>0.77568</td>
        <td>0.77633514</td>
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        <td>LogisticRegression</td>
        <td>0.963813486</td>
        <td>0.963569231</td>
        <td>0.963568212</td>
        <td>0.894006837</td>
        <td>0.89344</td>
        <td>0.893476045</td>
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        <td>Lightgbm</td>
        <td>0.973305629</td>
        <td>0.973169231</td>
        <td>0.973137628</td>
        <td>0.857553345</td>
        <td>0.85704</td>
        <td>0.857083816</td>
    </tr>
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        <td>XGBoost</td>
        <td>0.969366073</td>
        <td>0.969292308</td>
        <td>0.969247159</td>
        <td>0.853760967</td>
        <td>0.85208</td>
        <td>0.852217788</td>
    </tr>
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        <td>SVM</td>
        <td>0.964528812</td>
        <td>0.964307692</td>
        <td>0.964277496</td>
        <td>0.900594692</td>
        <td>0.90016</td>
        <td>0.900186524</td>
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        <td>CNN</td>
        <td>0.96</td>
        <td>0.96</td>
        <td>0.96</td>
        <td>0.861629649</td>
        <td>0.86128</td>
        <td>0.861255706</td>
    </tr>
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